Testing for the expected number of exceedances in strongly dependent seasonal time series

Jan Beran, Britta Steffens and Sucharita Ghosh

Journal of Nonparametric Statistics, 2021, vol. 33, issue 3-4, 417-434

Abstract: We consider seasonal time series models with a strongly dependent residual process. The question of testing for a change in the expected number of exceedances is addressed. Based on a functional limit theorem for seasonal empirical processes, a test of the null hypothesis of no change is proposed. The method is applied to daily temperature series at various locations in Switzerland. The test reveals interesting differences in the effect of global warming on seasonal temperature exceedances.

Date: 2021
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DOI: 10.1080/10485252.2021.1977301

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